Telecoms Unprepared for Big Data Evolution

According to a recent projection, the market for big data services by telecommunications companies will grow at a compound annual growth rate (CAGR) of more than 28% between 2018 and 2022.1 Another data market for telco companies, geographic information services, is expected to reach $3.27 billion by 2023, at a CAGR of 10.6%.2

The next stage of the big data revolution, coupled with the rollout of fifth-generation mobile technology, should present a golden opportunity to the telco sector,” says James D’Arezzo, CEO, Condusiv Technologies. D’Arezzo, whose company a leader in I/O reduction and SQL database performance, adds, “The question is whether the sector is in a financial position to take advantage of that opportunity.”

D’Arezzo is by no means alone in this assessment. A 2017 industry survey by PricewaterhouseCoopers noted that to a large extent, telecom companies have not succeeded in their efforts to monetize the flood of data running through their networks. Their services have become increasingly commoditized, and their ability to reinvest in network upgrades and digital advances has been severely constrained. At the same time, many carriers have tried to be all things to all people, delivering a wide variety of services to their customers. But as a group they have not managed to excel at any of those services, leaving them vulnerable to competition.3

A more recent study from Deloitte points out that for telecommunications carriers, revenue is of critical importance in 2018. Revenue yield on data services (revenue per bit consumed) continues to decline as consumers use more and more data, with static or declining monthly bills, making it critical to identify rapid investment opportunities across the telecom portfolio. For any major telecom provider, 5G will require major investment over the next several years, in addition to other areas such as IoT and cross-industry partnerships. Additionally, projections show a fourfold increase in mobile data traffic between 2016 and 2021; this suggests that an investment of $130 billion to $150 billion could be required over the period to adequately support broadband competition, rural coverage, and wireless densification. Carriers will also be obliged to continue to update legacy IT systems, particularly as they expand into new areas.4

While they’re doing all this, notes D’Arezzo, telecoms—publicly held companies in a highly price-competitive market—will also be under intense pressure to contain operating costs. One way to do this, he suggests, is to make certain that the core of the enterprise’s IT investment—its ability to process and analyze data—is functioning at maximum efficiency.

The telecoms are going to be making some heavy investments, including investments in hardware, whether onsite or in the cloud,” says D’Arezzo. “What they’re buying, finally, is data input and output at speed. That’s what computers do. There are software products—my company happens to make them—that can improve a storage and server system’s I/O 30% to 50% or more, with no additional hardware cost. Given the size of the investments they’re going to have to make, and the pressures in their market, I cannot too strongly recommend to anyone making strategic decisions for a telco that they incorporate this kind of software into their system planning. It can make a significant competitive difference.”

“+28% CAGR Growth to be achieved by Big Data For Telcos and Telecom market According to new research in industry,” Business Services News, May 8, 2018.

Resource Links:

Industry Perspectives

In this special guest feature, Assaf Katan, CEO & Co-Founder of Apertio, the Open Data deep search engine, suggests that there are huge social and financial benefits that businesses and economies can realize if they can successfully leverage Open Data. Despite this, there are still some hurdles for data professionals to leap. A great way to start is to consider whether your data meets the criteria for what’s known as the FAIR principles. These are Findability, Accessibility, Interoperability and Reusability. [READ MORE…]

White Papers

Databricks Unified Analytics Platform is a cloud-service designed to provide you with ready-to-use clusters that can handle all analytics processes in one place, from data preparation to model building and serving, with virtually no limit so that you can scale resources as needed. Download the new guide that walks readers through four practical end-to-end Machine Learning use cases on Databricks.